Aim: Online species distribution data, global or regional, are increasingly used in biodiversity studies although data limitations have been reported. We explore, for the two major databanks in our research region, how incomplete data are at a large taxonomic and geographic scale, how it is affected by spatial grain, and to what degree it affects inference from analyses of richness or turnover and the environment. Location: China.Major taxa studied: Vascular plants. Methods:We assembled species lists of all vascular plants from the Global Biodiversity Information Facility (GBIF) and the National Specimen Information Infrastructure (NSII) at three spatial scales (national, provincial, county). We determined the completeness of each compilation by comparing the number of species with that from inventory-based species list (for 28 provinces, 14 counties, and 146 nature reserves within counties). We related richness from each of the data sources (GBIF, NSII, inventory) to environmental variables (temperature, precipitation, elevational range) and compared regression models among the three data sources. We quantified floristic similarity between regions based on the three data sources and related species turnover to geographic and environmental distances.Results: Data incompleteness was prevalent at all spatial grains, but it increased with decreasing grain and it was higher for GBIF than for NSII. At the national scale, GBIF included 64.1% and NSII included 89.4% of true species richness in China. At the county scale these figures dropped to an average of 12.7% for GBIF and 60.0% for NSII. This changed the order and significance of environmental determinants of richness in regression models. The relationship between floristic similarity and geographic or environmental distance was shallower for GBIF and NSII, compared to inventory data. When the GBIF data were supplemented with the NSII data, the data completeness of GBIF increased from 64.1% to 90.8% at the national scale, *These authors contributed equally to this work.

Bacillus -like species are gram-positive bacteria that are ubiquitous in soils. Many of Bacillus -like bacteria are demonstrated as beneficial microbes widely used in industry and agriculture. However, the knowledge related to their diversity and distribution patterns in soils is still rudimentary. In this study, we developed a combined research method of using culture-dependent and high-throughput sequencing to investigate the composition and diversity of cultivable Bacillus -like bacterial communities across 26 soil samples obtained from the black soil zone in northeast China. Nearly all bacterial 16S rDNA sequences were classified into the order Bacillales. Fifteen genera were detected, with Bacillus , Paenibacillus , and Brevibacillus being the three most abundant genera. Although more than 2,000 OTUs were obtained across all samples, 33 OTUs were confirmed as the abundant species with a relative abundance over 5% in at least one sample. Pairwise analysis showed that the diversity of Bacillus -like bacterial communities were significantly and positively correlated with soil total carbon contents and soil sampling latitudes, which suggests that a latitudinal gradient diversity of Bacillus -like bacterial communities exists in the black soil zone. The principal coordinates analysis revealed that the Bacillus -like bacterial communities were remarkably affected by soil sampling latitudes and soil total carbon content. In general, this study demonstrated that a distinct biogeographic distribution pattern of cultivable Bacillus -like bacterial communities existed in the black soil zone, which emphasizes that the strategy of local isolation and application of beneficial Bacillus -like strains is rather important in black soil agriculture development.